About The Position

We are sharing a specialised part-time consulting opportunity for experienced materials science and materials engineering professionals with backgrounds in STEM problem review, graduate-level materials verification, scientific reasoning, technical evaluation, grading methodology, and structured quality assurance. This role supports current and upcoming remote consulting opportunities focused on AI-assisted STEM training data review, materials engineering problem evaluation, simulated research environment assessment, ground truth verification, grading rubric review, and high-quality project execution. Selected professionals will review complex STEM prompts, verify expert-level answers, assess model-generated reasoning trajectories, and provide detailed feedback based on materials science expertise and scientific judgment.

Requirements

  • MS or PhD in materials science, materials engineering, or a closely related technical field
  • Strong ability to independently verify ground truth solutions for graduate-level materials science or materials engineering problems
  • Experience reviewing technical problems, grading methodologies, solution explanations, model outputs, or structured STEM tasks
  • Strong scientific reasoning and ability to evaluate technical correctness, methodological soundness, and problem clarity
  • Ability to summarize complex model-generated reasoning trajectories clearly and objectively
  • Strong attention to detail and ability to identify subtle errors in reasoning, assumptions, calculations, material-property logic, or grading methodology
  • Comfort reviewing AI-generated STEM content and applying detailed evaluation criteria
  • Excellent written communication skills
  • Ability to work independently in a remote, asynchronous, project-based environment

Nice To Haves

  • Advanced expertise in one or more materials science or materials engineering subdomains, such as polymers, metals, ceramics, composites, biomaterials, nanomaterials, thermodynamics, phase transformations, crystallography, mechanical properties, electronic materials, or materials characterization
  • Experience teaching, grading, reviewing, or designing graduate-level materials engineering problems
  • Familiarity with rubric-based review, benchmark evaluation, technical QA, research-style assessment, or structured feedback workflows
  • Experience evaluating multi-step scientific solutions, materials-property calculations, experimental reasoning, symbolic derivations, or numerical verification
  • Ability to provide concise, actionable feedback for both technical correctness and training data quality

Responsibilities

  • Review complex STEM and materials engineering problem prompts for clarity, technical rigor, completeness, and suitability as training data
  • Independently verify ground truth answers for graduate-level materials science and materials engineering problems
  • Evaluate whether task prompts require appropriate domain reasoning, clear assumptions, and technically sound solution paths
  • Identify ambiguous wording, missing constraints, incorrect assumptions, incomplete derivations, or weak problem construction
  • Assess golden answers for correctness, completeness, scientific rigor, and alignment with the stated task requirements
  • Review grading criteria for robustness, objectivity, and consistency across acceptable solution approaches
  • Determine whether evaluation rubrics properly capture correct reasoning, valid alternatives, numerical tolerances, material-property considerations, and common error cases
  • Provide Accept, Revise, or Reject verdicts with concrete written explanations
  • Assess simulated research environments for scientific realism, construction quality, and diversity
  • Review seed prompts and multi-agent trajectories to evaluate whether research-style workflows are plausible and technically meaningful
  • Read and summarize model agent rollouts, including stronger and weaker solution attempts
  • Identify issues related to unrealistic reasoning, weak scientific setup, poor trajectory diversity, or insufficient materials-domain grounding
  • Provide clear written feedback explaining materials engineering reasoning, grading concerns, task-quality issues, and suggested improvements
  • Follow standardized review forms, detailed task instructions, and project-specific quality criteria accurately
  • Review discrete STEM QA deliverables within expected timelines
  • Collaborate through asynchronous project workflows to improve technical training data quality and AI-assisted STEM evaluation outputs

Benefits

  • Competitive compensation up to $85/hour
  • Remote work
  • Part-time project work
  • Opportunity to apply materials science and materials engineering expertise
  • Contribute to high-quality AI-assisted technical evaluation and training data development
  • Work on discrete deliverables aligned with subject-matter expertise and availability
  • Weekly payments via Stripe or Wise
  • Potential for project extension
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